classify_ai_system

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden. It discloses that the tool may ask the user or opt for a cautious answer when uncertain, and that it returns a structured 'scope finding'. These are meaningful behavioral traits beyond the basic function, though it doesn't discuss side effects (likely none) or detailed output schema specifics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences: first states the core purpose, second explains the mapping/flag behavior, third addresses uncertainty handling. Every sentence earns its place with no redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (7 params, no output schema), the description adequately covers purpose, return values (risk tier, obligations, deadlines, structured finding), and ambiguity handling. While it doesn't detail the structured finding's fields or differentiate from siblings, the schema's rich parameter descriptions complement the description well.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with detailed explanations for each boolean flag, so the baseline is 3. The description adds minimal parameter-level meaning, only mentioning mapping user descriptions to flags, which is somewhat vague. It doesn't compensate or enhance beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool classifies AI systems under the EU AI Act and returns risk tier, obligations, and deadlines. This specific verb+resource+output distinguishes it from sibling tools like eu_ai_act_timeline or explain_tier.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides some guidance on handling uncertainty ('ask the user or choose the more cautious answer') and hints at mapping user descriptions to boolean flags, but it does not explicitly contrast with sibling tools or state when to choose this tool over alternatives. The usage context is implied but exclusions/alternatives are missing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.